---------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  /Users/006489466/Dropbox/Mac/Downloads/AnalysisLog.log
  log type:  text
 opened on:  24 May 2023, 15:41:36

. do "/var/folders/rm/04tctgtx0bxg5jlm6dfv1ql80000gr/T//SD09247.000000"

. regress fear100 i.group i.gend i.race age if race != 7

      Source |       SS           df       MS      Number of obs   =       749
-------------+----------------------------------   F(20, 728)      =      9.17
       Model |  115705.638        20  5785.28188   Prob > F        =    0.0000
    Residual |  459066.888       728  630.586385   R-squared       =    0.2013
-------------+----------------------------------   Adj R-squared   =    0.1794
       Total |  574772.526       748  768.412468   Root MSE        =    25.111

-----------------------------------------------------------------------------------
          fear100 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
------------------+----------------------------------------------------------------
            group |
             CDF  |  -.1123308   4.663644    -0.02   0.981    -9.268126    9.043465
              CN  |  -5.337318   4.630152    -1.15   0.249    -14.42736    3.752725
              1%  |  -1.005285   4.656822    -0.22   0.829    -10.14769    8.137118
              4%  |  -3.141762   4.660463    -0.67   0.500    -12.29131    6.007789
              6%  |  -.3045738   4.681826    -0.07   0.948    -9.496066    8.886919
              9%  |  -2.004071    4.62785    -0.43   0.665     -11.0896    7.081453
             16%  |  -13.12411   4.650373    -2.82   0.005    -22.25385   -3.994365
             1%N  |  -7.526726   4.742618    -1.59   0.113    -16.83757    1.784115
             4%N  |  -1.571187   4.605232    -0.34   0.733    -10.61231    7.469934
             6%N  |  -.9841248   4.709604    -0.21   0.835    -10.23015    8.261901
             9%N  |  -4.847624    4.55863    -1.06   0.288    -13.79725    4.102007
            16%N  |  -3.600767    4.66919    -0.77   0.441    -12.76745    5.565918
                  |
             gend |
           Woman  |  -4.054894   1.937669    -2.09   0.037     -7.85898   -.2508084
      Gend. Exp.  |   7.473061   5.049702     1.48   0.139    -2.440655    17.38678
                  |
             race |
           Asian  |  -8.587976   10.91746    -0.79   0.432    -30.02144    12.84549
Black/Afr. Desc.  |   4.158677   9.231526     0.45   0.652    -13.96491    22.28227
 Hispanic/Latine  |  -.7308282   9.658966    -0.08   0.940    -19.69358    18.23192
           White  |  -13.32395   9.057269    -1.47   0.142    -31.10543    4.457537
    Multi-Racial  |  -7.522189   9.735298    -0.77   0.440     -26.6348    11.59042
                  |
              age |  -.4880927   .0605764    -8.06   0.000     -.607018   -.3691675
            _cons |   74.39005   9.696066     7.67   0.000     55.35447    93.42564
-----------------------------------------------------------------------------------

. 
. pwcompare group, mcompare(dunnett) effects

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

---------------------------
             |    Number of
             |  comparisons
-------------+-------------
       group |           12
---------------------------

-------------------------------------------------------------------------------
              |                             Dunnett              Dunnett
              |   Contrast   Std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
        group |
 CDF vs Ctrl  |  -.1123308   4.663644    -0.02   1.000    -13.02114    12.79648
  CN vs Ctrl  |  -5.337318   4.630152    -1.15   0.889    -18.15342    7.478789
  1% vs Ctrl  |  -1.005285   4.656822    -0.22   1.000    -13.89521    11.88464
  4% vs Ctrl  |  -3.141762   4.660463    -0.67   0.998    -16.04177    9.758245
  6% vs Ctrl  |  -.3045738   4.681826    -0.07   1.000    -13.26371    12.65457
  9% vs Ctrl  |  -2.004071    4.62785    -0.43   1.000    -14.81381    10.80566
 16% vs Ctrl  |  -13.12411   4.650373    -2.82   0.043    -25.99618   -.2520289
 1%N vs Ctrl  |  -7.526726   4.742618    -1.59   0.577    -20.65414    5.600685
 4%N vs Ctrl  |  -1.571187   4.605232    -0.34   1.000    -14.31832    11.17594
 6%N vs Ctrl  |  -.9841248   4.709604    -0.21   1.000    -14.02015     12.0519
 9%N vs Ctrl  |  -4.847624    4.55863    -1.06   0.931    -17.46576    7.770514
16%N vs Ctrl  |  -3.600767    4.66919    -0.77   0.994    -16.52493    9.323396
-------------------------------------------------------------------------------
Note: The dunnett method requires balanced data for proper level coverage. A
      factor was found to be unbalanced.

. 
. * want to create plots for cell means for visualization
. margins group // cell means

Predictive margins                                         Number of obs = 749
Model VCE: OLS

Expression: Linear prediction, predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
       group |
       Ctrl  |   42.59787   3.248135    13.11   0.000     36.22104     48.9747
        CDF  |   42.48553   3.345199    12.70   0.000     35.91815    49.05292
         CN  |   37.26055   3.304886    11.27   0.000      30.7723    43.74879
         1%  |   41.59258   3.344745    12.44   0.000     35.02608    48.15908
         4%  |    39.4561   3.339255    11.82   0.000     32.90039    46.01182
         6%  |   42.29329   3.352132    12.62   0.000     35.71229    48.87429
         9%  |   40.59379   3.295961    12.32   0.000     34.12307    47.06452
        16%  |   29.47376   3.335971     8.84   0.000     22.92449    36.02303
        1%N  |   35.07114   3.455058    10.15   0.000     28.28807    41.85421
        4%N  |   41.02668   3.265169    12.56   0.000     34.61641    47.43695
        6%N  |   41.61374   3.399819    12.24   0.000     34.93912    48.28836
        9%N  |   37.75024   3.204295    11.78   0.000     31.45948      44.041
       16%N  |    38.9971    3.34939    11.64   0.000     32.42148    45.57272
------------------------------------------------------------------------------

. marginsplot, recast(dot) ytitle("Fear of Police") title("")

Variables that uniquely identify margins: group

. 
. 
. 
. 
. 
. /*
> Interpretation: relative to the control condition, where no received
> information about the extent of deadly force, fear of police does not increase
> a substantial amount. the only time people seem more afraid of police, related to 
> shootings is in the category where 16% of all shootings involve unarmed civilains.
> However, this effect is null once one is given information about the extent of shootings
> in the US per year
> */
. 
. *regression where people choose not to disclose race
. regress legit100 i.group i.gend i.race age if race != 7

      Source |       SS           df       MS      Number of obs   =       749
-------------+----------------------------------   F(20, 728)      =      7.84
       Model |  69740.9239        20   3487.0462   Prob > F        =    0.0000
    Residual |  323600.017       728  444.505517   R-squared       =    0.1773
-------------+----------------------------------   Adj R-squared   =    0.1547
       Total |  393340.941       748  525.856872   Root MSE        =    21.083

-----------------------------------------------------------------------------------
         legit100 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
------------------+----------------------------------------------------------------
            group |
             CDF  |   .9093222    3.91554     0.23   0.816    -6.777775    8.596419
              CN  |   6.079854    3.88742     1.56   0.118    -1.552038    13.71175
              1%  |   .5261487   3.909812     0.13   0.893    -7.149704    8.202001
              4%  |   8.254292   3.912869     2.11   0.035     .5724383    15.93615
              6%  |  -.3776516   3.930806    -0.10   0.923    -8.094719    7.339416
              9%  |  -1.821989   3.885488    -0.47   0.639    -9.450088    5.806109
             16%  |   6.599686   3.904398     1.69   0.091    -1.065537    14.26491
             1%N  |    .809623   3.981846     0.20   0.839    -7.007648    8.626894
             4%N  |   5.535259   3.866498     1.43   0.153    -2.055558    13.12608
             6%N  |     5.5884   3.954128     1.41   0.158    -2.174453    13.35125
             9%N  |  -1.289645   3.827372    -0.34   0.736    -8.803648    6.224359
            16%N  |   6.316696   3.920196     1.61   0.108    -1.379543    14.01293
                  |
             gend |
           Woman  |  -3.996699   1.626844    -2.46   0.014    -7.190564   -.8028336
      Gend. Exp.  |  -19.30056    4.23967    -4.55   0.000      -27.624   -10.97713
                  |
             race |
           Asian  |   18.03921   9.166171     1.97   0.049     .0439229    36.03449
Black/Afr. Desc.  |   .8785988   7.750679     0.11   0.910    -14.33775    16.09495
 Hispanic/Latine  |   7.580447   8.109553     0.93   0.350    -8.340453    23.50135
           White  |   15.87228   7.604375     2.09   0.037       .94316     30.8014
    Multi-Racial  |   7.446487   8.173641     0.91   0.363    -8.600233    23.49321
                  |
              age |   .2806385   .0508592     5.52   0.000     .1807903    .3804868
            _cons |   27.05682   8.140702     3.32   0.001     11.07476    43.03887
-----------------------------------------------------------------------------------

. pwcompare group, mcompare(dunnett) effects

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

---------------------------
             |    Number of
             |  comparisons
-------------+-------------
       group |           12
---------------------------

-------------------------------------------------------------------------------
              |                             Dunnett              Dunnett
              |   Contrast   Std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
        group |
 CDF vs Ctrl  |   .9093222    3.91554     0.23   1.000    -9.928762    11.74741
  CN vs Ctrl  |   6.079854    3.88742     1.56   0.595    -4.680397    16.84011
  1% vs Ctrl  |   .5261487   3.909812     0.13   1.000    -10.29608    11.34838
  4% vs Ctrl  |   8.254292   3.912869     2.11   0.240      -2.5764    19.08498
  6% vs Ctrl  |  -.3776516   3.930806    -0.10   1.000    -11.25799    10.50269
  9% vs Ctrl  |  -1.821989   3.885488    -0.47   1.000    -12.57689    8.932912
 16% vs Ctrl  |   6.599686   3.904398     1.69   0.499    -4.207558    17.40693
 1%N vs Ctrl  |    .809623   3.981846     0.20   1.000    -10.21199    11.83124
 4%N vs Ctrl  |   5.535259   3.866498     1.43   0.699     -5.16708     16.2376
 6%N vs Ctrl  |     5.5884   3.954128     1.41   0.713    -5.356494    16.53329
 9%N vs Ctrl  |  -1.289645   3.827372    -0.34   1.000    -11.88368    9.304394
16%N vs Ctrl  |   6.316696   3.920196     1.61   0.559    -4.534278    17.16767
-------------------------------------------------------------------------------
Note: The dunnett method requires balanced data for proper level coverage. A
      factor was found to be unbalanced.

. margins group

Predictive margins                                         Number of obs = 749
Model VCE: OLS

Expression: Linear prediction, predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
       group |
       Ctrl  |   48.12527   2.727096    17.65   0.000     42.77136    53.47918
        CDF  |   49.03459   2.808589    17.46   0.000     43.52069     54.5485
         CN  |   54.20513   2.774743    19.54   0.000     48.75767    59.65258
         1%  |   48.65142   2.808208    17.32   0.000     43.13827    54.16457
         4%  |   56.37956   2.803599    20.11   0.000     50.87546    61.88367
         6%  |   47.74762    2.81441    16.97   0.000     42.22229    53.27295
         9%  |   46.30328    2.76725    16.73   0.000     40.87054    51.73603
        16%  |   54.72496   2.800842    19.54   0.000     49.22627    60.22365
        1%N  |    48.9349   2.900826    16.87   0.000     43.23991    54.62988
        4%N  |   53.66053   2.741397    19.57   0.000     48.27854    59.04252
        6%N  |   53.71367   2.854448    18.82   0.000     48.10974     59.3176
        9%N  |   46.83563   2.690288    17.41   0.000     41.55398    52.11728
       16%N  |   54.44197   2.812108    19.36   0.000     48.92116    59.96278
------------------------------------------------------------------------------

. marginsplot, recast(dot) ytitle("Police Legitimacy") title("")

Variables that uniquely identify margins: group

. 
. 
. 
. 
. /*
> After correcting for multiple comparisons relative to reference category, there 
> aren't any significant differecnes in legitimacy across experimental group. 
> */
. 
. 
. *regression where people choose not to disclose race
. regress coop100 i.group i.gend i.race age if race != 7

      Source |       SS           df       MS      Number of obs   =       749
-------------+----------------------------------   F(20, 728)      =      6.47
       Model |  67787.2389        20  3389.36195   Prob > F        =    0.0000
    Residual |  381353.707       728  523.837509   R-squared       =    0.1509
-------------+----------------------------------   Adj R-squared   =    0.1276
       Total |  449140.945       748  600.455809   Root MSE        =    22.887

-----------------------------------------------------------------------------------
          coop100 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
------------------+----------------------------------------------------------------
            group |
             CDF  |  -6.936209   4.250611    -1.63   0.103    -15.28113    1.408709
              CN  |   1.592408   4.220085     0.38   0.706    -6.692581    9.877398
              1%  |  -3.450693   4.244393    -0.81   0.416     -11.7834    4.882019
              4%  |   3.347421   4.247712     0.79   0.431    -4.991806    11.68665
              6%  |   .1822627   4.267183     0.04   0.966    -8.195191    8.559716
              9%  |  -3.110423   4.217987    -0.74   0.461    -11.39129    5.170448
             16%  |   3.643207   4.238515     0.86   0.390    -4.677965    11.96438
             1%N  |  -5.920753   4.322591    -1.37   0.171    -14.40699    2.565479
             4%N  |    4.56598   4.197373     1.09   0.277     -3.67442    12.80638
             6%N  |   4.008321   4.292501     0.93   0.351    -4.418837    12.43548
             9%N  |  -4.160893   4.154898    -1.00   0.317    -12.31791    3.996119
            16%N  |   3.815509   4.255666     0.90   0.370    -4.539333    12.17035
                  |
             gend |
           Woman  |   1.550256   1.766061     0.88   0.380    -1.916924    5.017436
      Gend. Exp.  |  -16.30964   4.602478    -3.54   0.000    -25.34535   -7.273925
                  |
             race |
           Asian  |   7.709195   9.950564     0.77   0.439    -11.82603    27.24442
Black/Afr. Desc.  |  -6.136499   8.413941    -0.73   0.466    -22.65498    10.38199
 Hispanic/Latine  |   2.218218   8.803525     0.25   0.801    -15.06511    19.50154
           White  |   4.020035   8.255117     0.49   0.626    -12.18664    20.22671
    Multi-Racial  |   .3712966   8.873098     0.04   0.967    -17.04862    17.79121
                  |
              age |   .3846872   .0552115     6.97   0.000     .2762945    .4930799
            _cons |   51.06883    8.83734     5.78   0.000     33.71911    68.41854
-----------------------------------------------------------------------------------

. pwcompare group, mcompare(dunnett) effects

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

---------------------------
             |    Number of
             |  comparisons
-------------+-------------
       group |           12
---------------------------

-------------------------------------------------------------------------------
              |                             Dunnett              Dunnett
              |   Contrast   Std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
        group |
 CDF vs Ctrl  |  -6.936209   4.250611    -1.63   0.543    -18.70176    4.829341
  CN vs Ctrl  |   1.592408   4.220085     0.38   1.000    -10.08865    13.27346
  1% vs Ctrl  |  -3.450693   4.244393    -0.81   0.990    -15.19903    8.297647
  4% vs Ctrl  |   3.347421   4.247712     0.79   0.993    -8.410105    15.10495
  6% vs Ctrl  |   .1822627   4.267183     0.04   1.000    -11.62916    11.99368
  9% vs Ctrl  |  -3.110423   4.217987    -0.74   0.996    -14.78567    8.564827
 16% vs Ctrl  |   3.643207   4.238515     0.86   0.985    -8.088863    15.37528
 1%N vs Ctrl  |  -5.920753   4.322591    -1.37   0.746    -17.88554    6.044036
 4%N vs Ctrl  |    4.56598   4.197373     1.09   0.921    -7.052209    16.18417
 6%N vs Ctrl  |   4.008321   4.292501     0.93   0.972     -7.87318    15.88982
 9%N vs Ctrl  |  -4.160893   4.154898    -1.00   0.954    -15.66151    7.339727
16%N vs Ctrl  |   3.815509   4.255666     0.90   0.979    -7.964033    15.59505
-------------------------------------------------------------------------------
Note: The dunnett method requires balanced data for proper level coverage. A
      factor was found to be unbalanced.

. margins group

Predictive margins                                         Number of obs = 749
Model VCE: OLS

Expression: Linear prediction, predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
       group |
       Ctrl  |   69.71637   2.960466    23.55   0.000      63.9043    75.52844
        CDF  |   62.78016   3.048934    20.59   0.000     56.79441    68.76591
         CN  |   71.30878   3.012191    23.67   0.000     65.39516     77.2224
         1%  |   66.26568    3.04852    21.74   0.000     60.28074    72.25062
         4%  |   73.06379   3.043516    24.01   0.000     67.08868    79.03891
         6%  |   69.89863   3.055252    22.88   0.000     63.90048    75.89679
         9%  |   66.60595   3.004057    22.17   0.000      60.7083     72.5036
        16%  |   73.35958   3.040523    24.13   0.000     67.39034    79.32882
        1%N  |   63.79562   3.149063    20.26   0.000     57.61329    69.97795
        4%N  |   74.28235   2.975991    24.96   0.000      68.4398     80.1249
        6%N  |   73.72469   3.098716    23.79   0.000     67.64121    79.80818
        9%N  |   65.55548   2.920509    22.45   0.000     59.82185     71.2891
       16%N  |   73.53188   3.052754    24.09   0.000     67.53863    79.52513
------------------------------------------------------------------------------

. marginsplot,recast(dot) ytitle("Cooperation") title("")

Variables that uniquely identify margins: group

. 
. 
. 
. 
. /*
> Interpretation: no changes in cooperation with police relative to control group
> */
. 
. *regression where people choose not to disclose race
. regress comp100 i.group i.gend i.race age if race !=7

      Source |       SS           df       MS      Number of obs   =       749
-------------+----------------------------------   F(20, 728)      =      4.74
       Model |   36951.789        20  1847.58945   Prob > F        =    0.0000
    Residual |  283755.548       728  389.774104   R-squared       =    0.1152
-------------+----------------------------------   Adj R-squared   =    0.0909
       Total |  320707.337       748  428.753124   Root MSE        =    19.743

-----------------------------------------------------------------------------------
          comp100 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
------------------+----------------------------------------------------------------
            group |
             CDF  |  -1.559607   3.666566    -0.43   0.671    -8.757913    5.638698
              CN  |   .7764267   3.640235     0.21   0.831    -6.370184    7.923038
              1%  |  -3.715624   3.661203    -1.01   0.311     -10.9034    3.472153
              4%  |   1.978298   3.664066     0.54   0.589    -5.215098    9.171694
              6%  |  -2.547534   3.680862    -0.69   0.489    -9.773905    4.678837
              9%  |   2.240444   3.638425     0.62   0.538    -4.902614    9.383503
             16%  |  -.2826598   3.656133    -0.08   0.938    -7.460482    6.895162
             1%N  |   1.766395   3.728656     0.47   0.636    -5.553808    9.086597
             4%N  |   1.585765   3.620643     0.44   0.662    -5.522383    8.693914
             6%N  |   2.727711   3.702701     0.74   0.462    -4.541534    9.996956
             9%N  |  -3.140966   3.584005    -0.88   0.381    -10.17718    3.895252
            16%N  |   2.661631   3.670927     0.73   0.469    -4.545235    9.868498
                  |
             gend |
           Woman  |     .01517   1.523399     0.01   0.992     -2.97561     3.00595
      Gend. Exp.  |  -12.51192   3.970086    -3.15   0.002    -20.30611    -4.71774
                  |
             race |
           Asian  |   16.44174   8.583332     1.92   0.056    -.4092967    33.29278
Black/Afr. Desc.  |   4.260712   7.257845     0.59   0.557    -9.988091    18.50952
 Hispanic/Latine  |   10.99953   7.593899     1.45   0.148    -3.909026    25.90808
           White  |   11.06743   7.120844     1.55   0.121    -2.912412    25.04727
    Multi-Racial  |   5.218062   7.653912     0.68   0.496    -9.808311    20.24444
                  |
              age |   .3050377   .0476253     6.40   0.000     .2115384     .398537
            _cons |   41.26858   7.623068     5.41   0.000     26.30276    56.23439
-----------------------------------------------------------------------------------

. pwcompare group, mcompare(dunnett) effects

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

---------------------------
             |    Number of
             |  comparisons
-------------+-------------
       group |           12
---------------------------

-------------------------------------------------------------------------------
              |                             Dunnett              Dunnett
              |   Contrast   Std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
        group |
 CDF vs Ctrl  |  -1.559607   3.666566    -0.43   1.000    -11.70854    8.589327
  CN vs Ctrl  |   .7764267   3.640235     0.21   1.000    -9.299623    10.85248
  1% vs Ctrl  |  -3.715624   3.661203    -1.01   0.949    -13.84971    6.418465
  4% vs Ctrl  |   1.978298   3.664066     0.54   1.000    -8.163714    12.12031
  6% vs Ctrl  |  -2.547534   3.680862    -0.69   0.998    -12.73604    7.640969
  9% vs Ctrl  |   2.240444   3.638425     0.62   0.999    -7.830596    12.31149
 16% vs Ctrl  |  -.2826598   3.656133    -0.08   1.000    -10.40271    9.837394
 1%N vs Ctrl  |   1.766395   3.728656     0.47   1.000    -8.554403    12.08719
 4%N vs Ctrl  |   1.585765   3.620643     0.44   1.000    -8.436055    11.60759
 6%N vs Ctrl  |   2.727711   3.702701     0.74   0.996    -7.521241    12.97666
 9%N vs Ctrl  |  -3.140966   3.584005    -0.88   0.982    -13.06137     6.77944
16%N vs Ctrl  |   2.661631   3.670927     0.73   0.996    -7.499373    12.82264
-------------------------------------------------------------------------------
Note: The dunnett method requires balanced data for proper level coverage. A
      factor was found to be unbalanced.

. margins group

Predictive margins                                         Number of obs = 749
Model VCE: OLS

Expression: Linear prediction, predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
       group |
       Ctrl  |   63.33614   2.553691    24.80   0.000     58.32266    68.34961
        CDF  |   61.77653   2.630003    23.49   0.000     56.61323    66.93982
         CN  |   64.11256   2.598308    24.67   0.000     59.01149    69.21363
         1%  |   59.62051   2.629646    22.67   0.000     54.45792     64.7831
         4%  |   65.31443   2.625329    24.88   0.000     60.16031    70.46855
         6%  |    60.7886   2.635453    23.07   0.000     55.61461     65.9626
         9%  |   65.57658   2.591292    25.31   0.000     60.48928    70.66388
        16%  |   63.05348   2.622748    24.04   0.000     57.90442    68.20253
        1%N  |   65.10253   2.716374    23.97   0.000     59.76967    70.43539
        4%N  |    64.9219   2.567082    25.29   0.000     59.88213    69.96167
        6%N  |   66.06385   2.672945    24.72   0.000     60.81625    71.31145
        9%N  |   60.19517   2.519223    23.89   0.000     55.24936    65.14098
       16%N  |   65.99777   2.633298    25.06   0.000       60.828    71.16753
------------------------------------------------------------------------------

. marginsplot, recast(dot) ytitle("Compliance") title("")

Variables that uniquely identify margins: group

. 
end of do-file

. log close
      name:  <unnamed>
       log:  /Users/006489466/Dropbox/Mac/Downloads/AnalysisLog.log
  log type:  text
 closed on:  24 May 2023, 15:42:06
---------------------------------------------------------------------------------------------
